Hybrid Optimal Control of Homogeneous Epidemiological Compartmental Models with Regime Switching

TL;DR

This paper formulates a hybrid optimal control problem for epidemiological models incorporating multiple intervention phases, including work-from-home and vaccination, to optimize disease mitigation strategies.

Contribution

It introduces a novel hybrid control framework with phase-dependent dynamics and switchings, applying the Hybrid Minimum Principle to optimize intervention timing and policies.

Findings

Coordinating WFH and vaccination improves disease mitigation.

Hybrid control captures policy escalation and relaxation phases.

Numerical results show enhanced mitigation over single-phase strategies.

Abstract

Optimal intervention design is formulated as a hybrid optimal control problem for multiphase homogeneous epidemiological systems. The system extends a foundational compartmental model through intermediate phases that incorporate work-from-home (WFH) policies and a vaccination protocol, yielding a four-phase hybrid system that captures policy escalation and relaxation. Key characteristics of the resulting hybrid system include (i) phase-dependent continuous dynamics and running costs that respectively capture distinct disease transmission mechanisms and shifting public health socioeconomic trade-offs, (ii) a combination of autonomous and controlled switchings for intervention policies, whose times are co-optimized - whether indirectly via state thresholds or directly as decision variables alongside continuous inputs to minimize the overall cost, and (iii) nontrivial state jump maps that govern transitions between phases with differing state and control space dimensions. The Hybrid Minimum Principle (HMP) is invoked to obtain the optimal solutions. Numerical results demonstrate that coordinating WFH policies with vaccination efforts provides improved mitigation of disease spread compared to single-phase policy interventions.